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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Graduate School
  2. Department of Business Administration
  3. Master of Science (MSc) in Quantitative Methods
  4. Course Structure Diagram with Credits
  5. Multivariate Statistics
  6. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
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Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
SAY530 - Multivariate Statistics II. SEMESTER 3 +0 6.0
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) DOÇ. DR. DUYGU TUNALI
Mode of Delivery This course requires face-to-face classes.
Place of Delivery
Used Educational Platforms
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended Statistics and Regression Analysis are the recommended components for this course.
Recommended Resources -
Work Placement Not suitable for this course
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Introduction: Organization of data set, Descriptive statistics, Graphical techniques
Week - 2 Multivariate Normal Distribution: Properties, Maximum likelihood estimation
Week - 3 Principal Component Analysis: Dimension reduction
Week - 4 Principal Component Analysis:Steps to be followed
Week - 5 Introduction to Factor Analysis and comparison with Principal Component Analysis
Week - 6 Factor analysis; Factor Rotation and Factor Scores
Week - 7 Factor analysis; Application
Week - 8 Logistic Regression and Classification
Week - 9 Logit model, Binary logistic regression
Week - 10 Sample review
Week - 11 Multiple logistic regression
Week - 12 Sample review
Week - 13 Overall evaluation
Week - 14 Overall evaluation

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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